summary.ssanova {gss}R Documentation

Assessing Smoothing Spline ANOVA Fits

Description

Calculate various summaries of smoothing spline ANOVA fits.

Usage

summary[.ssanova](obj, diagnostics=FALSE)

Arguments

obj Object of class "ssanova".
diagnostics Flag indicating if diagnostics are required.

Value

summary.ssanova returns a list object of class "summary.ssanova" consisting of the following components. The entries pi, kappa, cosines, and roughness are only calculated if diagnostics=TRUE; see the reference below for details concerning the diagnostics.

call Fitting call.
method Method for smoothing parameter selection.
fitted Fitted values.
residuals Residuals.
sigma Assumed or estimated error standard deviation.
r.squared Fraction of "explained variance" by the fitted model.
rss Residual sum of squares.
penalty Roughness penalty associated with the fit.
pi "Percentage decomposition" of "explained variance" into model terms.
kappa Concurvity diagnostics for model terms. Virtually the square roots of variance inflation factors of a retrospective linear model.
cosines Cosine diagnostics for practical significance of model terms.
roughness Percentage decomposition of the roughness penalty penalty into model terms.

Author(s)

Chong Gu, chong@stat.purdue.edu

References

Gu, C. (1992), Diagnostics for nonparametric regression models with additive terms. Journal of the American Statistical Association, 87, 1051–1058.

See Also

Fitting function ssanova and methods predict.ssanova, fitted.ssanova.